it would be amazing if you could make a video tutorial on ELK installation with Docker and Helm charts. Your expertise is highly valued. Seeing your smile makes my day brighter :)
Why thank you for the kind words! Regarding your request, We plan to make a few videos on kubernetes in the near future and helm charts will "probably" be covered in that discussion. :) Thanks for the suggestions! Have a great day
Great video, you taught both theory and showed a practical example. I was just wondering about the persistence capacity of ES, what amount of data is it ok to have directly on ES and when/how to have a DB connected to it.
ES can handle a lot of data. Asking when to have DB connected to it because of data size is not really the right question to ask. It can shard and replicate data, rebalance it, and much more. If you need help with ES/scaling/arch, feel free to get in touch via sematext.com ...
May God guide you to the truth, never I came across such a beautiful explanation on sharding, that's super simple. Thank you, do you have a video to implement elasticsearch with postgresql?
Useful thank you, but for what seemed like a fairly modest amount of sample data, it took almost third of a second to do the searching. Is this mostly an "overhead" and searching 1000 times as much data would only take a millisecond or so more - of could this then take many seconds / minutes to get the result. As this is suitable for Search Engines, I am guessing the 315ms was misleading somehow, but a brief comment about why this (seems) to take a long time for such a modest amount of data would be really helpful please. I am guessing I missed something important, but would welcome a pointer :)
Without rewatching our video, I assume this is referring to search latency from some example in the video? If so, I would not take those numbers so "literally" -- there are numerous factors that affect performance. Please don't extrapolate performance numbers from an example in a video.
This video is extremely underrated!
Thanks for this high quality content!
Great to hear this, thanks! :)
Found this video to be better than most of the other "What is Elastic search?" videos. Great explanation!
Glad it was helpful! Nice freediving profile pic there, @adityasagam-yo3fv :)
So glad this is Clear English and easy to follow and understand, without a distracting accent to decipher through.
*Liked & SUBSCIBED*
Very very good getting started tutorial!! 👍⚡
Glad you found it helpful!
Hello, where can I find the dummy data, you mentioned that there is a link below, but I did not find any link to it in the description
+1
it would be amazing if you could make a video tutorial on ELK installation with Docker and Helm charts. Your expertise is highly valued.
Seeing your smile makes my day brighter :)
Why thank you for the kind words!
Regarding your request, We plan to make a few videos on kubernetes in the near future
and helm charts will "probably" be covered in that discussion. :)
Thanks for the suggestions! Have a great day
great tutorials!
also interested inot architecture of es and what type of node better use for logs storage
Great video, you taught both theory and showed a practical example. I was just wondering about the persistence capacity of ES, what amount of data is it ok to have directly on ES and when/how to have a DB connected to it.
ES can handle a lot of data. Asking when to have DB connected to it because of data size is not really the right question to ask. It can shard and replicate data, rebalance it, and much more. If you need help with ES/scaling/arch, feel free to get in touch via sematext.com ...
May God guide you to the truth, never I came across such a beautiful explanation on sharding, that's super simple. Thank you, do you have a video to implement elasticsearch with postgresql?
why don't elastic search have a native monitoring tool like your sematext
good content, superb presentation!
Thank you kindly!
Useful thank you, but for what seemed like a fairly modest amount of sample data, it took almost third of a second to do the searching. Is this mostly an "overhead" and searching 1000 times as much data would only take a millisecond or so more - of could this then take many seconds / minutes to get the result.
As this is suitable for Search Engines, I am guessing the 315ms was misleading somehow, but a brief comment about why this (seems) to take a long time for such a modest amount of data would be really helpful please. I am guessing I missed something important, but would welcome a pointer :)
Without rewatching our video, I assume this is referring to search latency from some example in the video? If so, I would not take those numbers so "literally" -- there are numerous factors that affect performance. Please don't extrapolate performance numbers from an example in a video.
Wonderful
Good job!
Thanks!
"I will show you easier way"
and long and long long giberish terminal code :)
mind blowing 🤯
Ooops. Thanks for the feedback.
Can it be used for ai agents?? 🎉
@free_thinker4958 What are you referring to when you say "ai agents"?
In a matter of a few seconds, this guy goes from "you put different segments on each node" to "you put different shards on each node". Which is it????
@gdevelek Shards